Smart water meter management system based on open source Hongmeng

Abstract

The present invention discloses an intelligent water meter management system based on open source Hongmeng, which relates to the field of digital information transmission technology, including an analysis module, an early warning module and a control module. The analysis module obtains original data, extracts features and performs analysis to generate analysis results, and performs monitoring based on preset monitoring rules. When the analysis result shows an abnormality, an abnormal signal is output and transmitted to the early warning module. After receiving the abnormal signal, an early warning message is generated according to the preset early warning rule and sent to the administrator terminal, and a control instruction is simultaneously generated according to the early warning information and sent to the control module. According to the control instruction, the intelligent water meter is controlled and verified according to the preset strategy. Through multi-dimensional feature extraction and dynamic threshold adjustment, abnormal water use can be accurately identified and the false alarm rate can be reduced. The three-level warning is pushed in real time through pop-up windows and voice, and the response is to the minute level to avoid "one size fits all". With the help of Hongmeng communication, the abnormality type is distinguished, the positioning accuracy is high, the linkage terminal reduces the operation and maintenance cost, and the hardware compatibility reduces the expansion cost.

Description

Technical Field

[0001] The present invention relates to the field of digital information transmission technology, and in particular to an intelligent water meter management system based on open source Hongmeng. Background Art

[0002] With the deep integration of Internet of Things technology and smart metering needs, the field of water management is accelerating its transformation towards digitalization and intelligence. As the core terminal equipment of smart water management, smart water meters need to realize high-precision data collection, real-time status monitoring and dynamic control functions.

[0003] Traditional smart water meter management systems face several significant challenges in practical applications. First, data collection and analysis capabilities are significantly limited. Relying on a single sensor to capture instantaneous flow, they lack refined analysis of water usage time series, such as single duration, interval frequency, and cumulative volume. This makes it difficult to identify periodic water anomalies, such as nighttime micro-leaks. Furthermore, thresholds are often fixed and cannot be dynamically adjusted based on user type, seasonal variations, or historical water usage patterns, leading to false or missed alarms. Second, abnormality response mechanisms are sluggish, with long detection cycles. Alerts are communicated solely through text messages, lacking a multi-level warning system with red, yellow, and blue levels and visual presentation. This results in low response efficiency, a single control mechanism capable of only opening and closing valves, and an inability to implement differentiated control based on abnormality levels, potentially leading to over-intervention or under-control. Furthermore, the system suffers from insufficient connectivity and scalability, operating primarily independently and lacking a multi-meter linkage verification mechanism, making it difficult to distinguish between user-side and regional pipe network issues. Hardware compatibility is poor, communication protocols are inconsistent, and the system relies on local storage, limiting data sharing and remote management. At the same time, user interaction and operation and maintenance efficiency are low, there is a lack of user-side interactive interfaces, and self-inspection cannot be actively guided. Operation and maintenance rely on manual investigation, which is costly. System upgrades require physical contact with equipment, and threshold updates lack flexibility, making it difficult to adapt to changes in policies or water usage habits. Summary of the Invention

[0004] The technical problem addressed by the present invention is that traditional smart water meter management systems suffer from several significant problems in practical applications. First, data collection and analysis capabilities are significantly limited. Relying on a single sensor to collect instantaneous flow, they lack refined analysis of water use time series, such as single duration, interval frequency, and cumulative volume. This makes it difficult to identify periodic water use anomalies, such as nighttime micro-leaks. Furthermore, thresholds are often fixed and cannot be dynamically adjusted based on user type, seasonal variations, or historical water use patterns, which can easily lead to false alarms or missed alarms. Second, the abnormality response mechanism is sluggish, with long abnormality detection cycles. Warnings are only sent through a single channel, such as text messages. There is a lack of multi-level warning grading and visualization, including red / yellow / blue warnings. This results in low response efficiency. Control measures are limited to valve opening and closing, and differentiated control cannot be implemented based on abnormality levels, potentially leading to over-intervention or under-control. Furthermore, the system lacks interoperability and scalability, operates independently, and lacks a multi-meter interoperability verification mechanism, making it difficult to distinguish between user-side and regional pipe network issues. Hardware compatibility is poor, communication protocols are inconsistent, and the system relies on local storage, limiting data sharing and remote management. At the same time, user interaction and operation and maintenance efficiency are low, there is a lack of user-side interactive interfaces, and self-inspection cannot be actively guided. Operation and maintenance rely on manual investigation, which is costly. System upgrades require physical contact with equipment, and threshold updates lack flexibility, making it difficult to adapt to changes in policies or water usage habits.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: an intelligent water meter management system based on open source Hongmeng, including an analysis module, an early warning module and a control module;

[0006] The analysis module is used to obtain raw data, extract features and perform analysis, generate analysis results, perform monitoring based on preset monitoring rules, and output an abnormality signal when the analysis result shows an abnormality and transmit it to the early warning module;

[0007] The warning module, after receiving the abnormal signal, generates warning information according to the preset warning rules and sends it to the administrator terminal, and simultaneously generates control instructions according to the warning information and sends them to the control module;

[0008] The control module controls the smart water meter according to the control instruction and a preset strategy and performs verification.

[0009] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, the raw data includes instantaneous water consumption, cumulative water consumption and water use time data;

[0010] The instantaneous water consumption is collected by the built-in flow sensor of the smart water meter;

[0011] The accumulated water consumption and water use time data are collected by a timing unit.

[0012] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, the feature extraction and analysis of the raw data to generate the analysis results specifically include:

[0013] Extracting the peak value, average value and fluctuation coefficient of the instantaneous water consumption;

[0014] Calculate the duration of a single water use;

[0015] Count the time interval between two adjacent water use;

[0016] Extract the average flow rate during night time;

[0017] Calculate the daily growth rate of the cumulative water consumption;

[0018] When any characteristic value exceeds the corresponding preset threshold, an abnormal signal is output to the early warning module;

[0019] The characteristic values ​​include peak value, average value, fluctuation coefficient, duration of single water use, time interval between two adjacent water uses, average flow rate during night time and daily growth rate of cumulative water use.

[0020] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, the preset threshold includes:

[0021] Instantaneous water consumption thresholds, including peak thresholds, fluctuation coefficient thresholds, and nighttime flow thresholds;

[0022] Cumulative water consumption thresholds, including daily growth rate thresholds;

[0023] Water usage time data thresholds include:

[0024] Water use time interval thresholds, including peak hour interval thresholds and nighttime interval thresholds;

[0025] Water usage duration threshold, including the maximum duration threshold for a single water use and the water leakage duration threshold.

[0026] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, the abnormal signal is divided into level 1 abnormal signal, level 2 abnormal signal and level 3 abnormal signal based on the level.

[0027] The first-level abnormal signal corresponds to the instantaneous flow rate sudden over-limit abnormality, which is triggered and output when the instantaneous water consumption peak exceeds the first proportional threshold of the peak threshold or the fluctuation coefficient exceeds a;

[0028] The secondary abnormal signal corresponds to a continuous abnormality in the cumulative amount or an abnormality in high-frequency water use, and is triggered and output when the daily growth rate of the cumulative water consumption exceeds the second proportional threshold of the daily growth rate threshold of the cumulative water consumption for b consecutive days, or when the time interval between two adjacent water consumptions is lower than the third proportional threshold of the peak period interval threshold;

[0029] The third-level abnormal signal corresponds to abnormal trace continuous water use, and is triggered and output when the average flow rate during the night period is lower than the night flow threshold and the duration of a single water use during the night period exceeds the water leakage duration threshold.

[0030] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, the preset warning rules include:

[0031] Level 1 abnormal signal uses a red warning sign;

[0032] Level 2 abnormal signal uses yellow warning sign;

[0033] Level 3 abnormal signal uses a blue warning sign.

[0034] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, the warning module sends warning information to the administrator terminal in the form of a pop-up window and voice broadcast, and simultaneously sends corresponding control instructions to the control module;

[0035] The warning information includes abnormal signal level, abnormal type, abnormal occurrence time, and abnormal water usage data details.

[0036] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, wherein: the control instruction includes a first control instruction, a second control instruction and a third control instruction;

[0037] The control instruction priorities include:

[0038] The first control instruction has a high priority;

[0039] The second control instruction has a medium priority;

[0040] The third control instruction has a low priority;

[0041] The first control instruction is to immediately close the smart water meter valve;

[0042] The second control instruction is to limit the instantaneous water flow to 50% of the rated flow value, and the rated flow value is the maximum allowable flow value preset when the smart water meter leaves the factory;

[0043] The third control instruction is to generate a water use abnormality prompt and push it to the user terminal.

[0044] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, the preset strategy includes:

[0045] When a first control instruction corresponding to a first-level abnormal signal is received, the smart water meter valve is immediately closed, and the water meter status is continuously monitored at intervals of c seconds after the valve is closed. If the abnormality is not resolved within d seconds and an abnormal signal is still detected, a second control instruction is triggered to temporarily limit the flow rate to a fourth proportional threshold of the rated flow value;

[0046] When the second control instruction corresponding to the second-level abnormal signal is received, the flow restriction operation is performed first, and the warning information is pushed to the user terminal simultaneously;

[0047] When the third control instruction corresponding to the third-level abnormal signal is received, only the water use abnormality prompt is sent to the user terminal, and the valve closing or flow restriction operation is not performed temporarily. If the user does not respond to the prompt within e hours, the abnormal signal level will be upgraded to a second-level abnormal signal and the second control instruction will be executed.

[0048] As a preferred solution of the open source Hongmeng-based smart water meter management system described in the present invention, after the control instruction is executed, the timing function of the timing unit is used to periodically verify whether the abnormal signal is released according to the verification period, and determine whether to maintain, adjust or cancel the current control instruction based on the verification result;

[0049] The verification cycle includes:

[0050] The verification period for the first-level abnormal signal is f minutes;

[0051] The verification period for the secondary abnormal signal is g minutes;

[0052] The verification period for the third-level abnormal signal is h minutes;

[0053] The abnormal signal removal judgment adopts a progressive verification rule, specifically including basic data feature verification, water use data association verification and multi-water meter linkage verification;

[0054] The basic data feature verification periodically extracts the peak value, average value and fluctuation coefficient of instantaneous water consumption within each verification cycle, calculates the duration of a single water use, the time interval between two adjacent water uses and the daily growth rate of cumulative water consumption, and compares them with the preset threshold value;

[0055] If any characteristic value is higher or lower than the corresponding preset threshold, the abnormal judgment is maintained and the basic data characteristic verification of the next verification cycle continues;

[0056] If all characteristic values ​​meet the corresponding threshold requirements, the water use data association verification is carried out;

[0057] If the water use data association verification triggers an exception, return to the basic data feature verification;

[0058] If the water usage data association verification does not trigger an exception, the multi-water meter linkage verification is performed;

[0059] The multi-water meter linkage verification obtains the regional water supply pipeline pressure sensor data and the water consumption data of other surrounding smart water meters through wireless communication technology or wired communication technology during the verification period;

[0060] During the same verification cycle, if the pipe network pressure fluctuation exceeds the first pressure fluctuation range threshold or the surrounding smart water meter exceeds the fifth ratio threshold and abnormal flow occurs, it is determined to be a regional problem, triggering an abnormal return to basic verification;

[0061] If only a single smart water meter is abnormal and the pipe network pressure is normal, it is determined to be a user-side problem, the abnormality is resolved, and the control instruction is revoked.

[0062] The beneficial effects of the present invention are as follows: through multi-dimensional feature extraction and sliding window algorithm, combined with historical data and industry standards, the threshold is dynamically adjusted to accurately identify abnormal water use, and the false alarm rate is reduced compared with traditional solutions. The threshold can be automatically calibrated according to the season and water use trend. A three-level abnormal signal classification is adopted, and real-time push is pushed through pop-ups and voice. The response time is shortened to minutes, and the control instructions are linked with the levels to avoid "one size fits all". With the help of Hongmeng's distributed communication capabilities, multi-device data is obtained in real time. Combined with progressive verification rules, user-side and regional anomalies are distinguished to improve positioning accuracy. User terminal linkage is realized based on the Hongmeng ecosystem to guide autonomous investigation and reduce operation and maintenance costs. The hardware unifies the protocol through the HDF driver framework to reduce expansion costs and significantly improve system maintainability. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A three-dimensional diagram of a smart water meter provided by an embodiment of the present invention;

[0064] Figure 2 A schematic diagram of the basic process of a smart water meter management system based on open source Hongmeng is provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0065] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0066] Example 2, reference Figure 2 , as an embodiment of the present invention, provides an intelligent water meter management system based on open source Hongmeng, including: an analysis module, an early warning module and a control module;

[0067] The analysis module is used to obtain raw data, extract features and analyze them, generate analysis results, and perform monitoring based on preset monitoring rules. When the analysis results show an abnormality, it outputs an abnormality signal and transmits it to the early warning module;

[0068] The early warning module, after receiving the abnormal signal, generates early warning information according to the preset early warning rules and sends it to the administrator terminal, and simultaneously generates control instructions based on the early warning information and sends them to the control module;

[0069] The control module controls the smart water meter according to the preset strategy based on the control instructions and performs verification.

[0070] In one of the embodiments, the analysis module obtains raw data and extracts analysis features, identifies abnormal feature values, generates analysis results, and determines whether to trigger an abnormal signal based on preset monitoring rules. If it is determined to be abnormal, the abnormal signal is output to the early warning module to achieve accurate detection of abnormal water use. After receiving the abnormal signal, the early warning module generates early warning information according to the preset early warning rules and pushes it to the administrator terminal and simultaneously generates control instructions, so as to promptly notify the administrator and trigger the control process. After receiving the instruction, the control module controls the smart water meter according to the preset strategy and periodically verifies the control effect to ensure that the abnormal signal is effectively resolved.

[0071] The original data includes instantaneous water consumption, cumulative water consumption and water consumption time data;

[0072] The instantaneous water consumption is collected through the built-in flow sensor of the smart water meter;

[0073] The accumulated water consumption and water usage time data are collected through the timing unit.

[0074] In one embodiment, instantaneous water consumption is collected by an ultrasonic flow sensor built into the smart water meter. The ultrasonic flow sensor uses the propagation characteristics of ultrasonic waves in water flow to accurately measure the flow rate, and then derive the instantaneous water consumption. The sensor is located in the water flow channel and collects information once per second. The flow sensor communicates with the main control module through the driver framework (HDF) of the Hongmeng system. The timing unit is located in the main control unit inside the water meter and adopts a hardware structure with an integrated independent clock chip to ensure high precision and stability of timing. From the start of the water meter activation, the cumulative water consumption is calculated based on the instantaneous water consumption. The timing unit is implemented based on the high-precision timer service of the Hongmeng system, with a time accuracy error of less than 1 millisecond. The timing starts when the instantaneous water consumption is greater than 0 when the water use behavior occurs, and stops when the instantaneous water consumption is equal to 0 to record the duration of a single water use. The time interval between two adjacent water uses is the time difference between the two instantaneous water consumption changing from 0 to greater than 0, and the time interval between two adjacent water uses is monitored in real time.

[0075] Extract and analyze the features of the original data to generate analysis results, including:

[0076] Extract the peak value, average value and fluctuation coefficient of instantaneous water consumption;

[0077] Calculate the duration of a single water use;

[0078] Count the time interval between two adjacent water use;

[0079] Extract the average flow rate during night time;

[0080] Calculate the daily growth rate of cumulative water consumption;

[0081] When any characteristic value exceeds the corresponding preset threshold, an abnormal signal is output to the early warning module;

[0082] The characteristic values ​​include peak value, average value, fluctuation coefficient, duration of single water use, time interval between two adjacent water uses, average flow rate during night time and daily growth rate of cumulative water consumption.

[0083] In one embodiment, when extracting features and analyzing the original data to generate analysis results, one day is used as the statistical period. First, the peak value, average value and fluctuation coefficient of the instantaneous water consumption are extracted, where the fluctuation coefficient is obtained by calculating the ratio of the standard deviation of the instantaneous water consumption within the period to the average value. The standard deviation and average value are calculated using a sliding window algorithm with a window size of 24 hours. The statistical value is updated once each new data point is added, and outliers exceeding 3 times the standard deviation are eliminated before calculation. The duration of a single water use is then calculated based on the water use time data, and the time interval between two adjacent water uses is counted. The night time period is then filtered out from the daily data, defined as the data from 22:00 on the current day to 6:00 on the next day, and the average flow rate during this period is extracted. At the same time, the daily growth rate of the cumulative water consumption is calculated based on the cumulative water consumption, and the calculation formula is: (cumulative water consumption on the current day - cumulative water consumption on the previous day) / cumulative water consumption on the previous day The daily cumulative water consumption is calculated by accumulating the instantaneous water consumption from the time the water meter is activated to 24:00 on the same day. The data of the previous day is stored in the distributed database of the open source Hongmeng system. If the newly generated data reaches a certain amount during the statistical period, for example, 100 instantaneous water consumption data are collected, the calculation process is started immediately. When any of the above characteristic values ​​exceeds the corresponding preset threshold, the analysis module outputs an abnormal signal to the early warning module. The preset threshold is dynamically adjusted according to the water meter type, the user's historical water use pattern and industry standards, and is stored in the configuration center of the open source Hongmeng system. It can be updated through the remote management platform. These characteristic values ​​cover peak value, average value, fluctuation coefficient, duration of single water use, time interval between two adjacent water uses, average flow rate during night time and daily growth rate of cumulative water consumption. The analysis result is the system's comparison result based on the characteristic value and the preset threshold.

[0084] The preset thresholds include:

[0085] Instantaneous water consumption thresholds, including peak thresholds, fluctuation coefficient thresholds, and nighttime flow thresholds;

[0086] Cumulative water consumption thresholds, including daily growth rate thresholds;

[0087] Water usage time data thresholds include:

[0088] Water use time interval thresholds, including peak hour interval thresholds and nighttime interval thresholds;

[0089] Water usage duration threshold, including the maximum duration threshold for a single water use and the water leakage duration threshold.

[0090] In one embodiment, the preset thresholds include instantaneous water consumption thresholds, where the peak threshold is set according to the water meter specifications and user type. For example, the peak threshold for residential users is set to 3m³ / h, and for commercial users is set to 8m³ / h; the fluctuation coefficient threshold is set to 3.0, which is used to measure the variation of instantaneous water consumption; the night flow threshold is set to 0.03m³ / h during the night period (22:00 to 6:00 the next day). If it is lower than 0.03m³ / h, there may be a risk of water leakage. In terms of the cumulative water consumption threshold, the daily growth rate threshold is set to 25%. If If the daily cumulative water consumption increases by more than this ratio compared to the previous day, it is considered an anomaly. In the water use time data threshold, the peak hours are defined as 7:00-9:00 and 17:00-19:00 on weekdays, the interval threshold is set to 20 minutes, and the nighttime interval threshold is set to 120 minutes. When the time interval between two consecutive water uses is lower than the corresponding threshold, the system will conduct further verification. In the single water use duration threshold, the maximum duration threshold for a single water use is set to 90 minutes, and the water leakage duration threshold is set to 40 minutes. Once the water use duration exceeds the corresponding threshold, an anomaly judgment is triggered.

[0091] The threshold can be dynamically updated through the remote management platform. The update trigger conditions include: based on the changes in seasonal water usage patterns, the system adjusts the threshold when alternating between spring and summer and autumn and winter (using meteorological standards, when the average daily temperature is greater than or equal to 22°C for 5 consecutive days, it enters summer, and when it is less than or equal to 10°C, it enters winter, and the rest is spring / autumn); when the user's water usage data shows a stable new trend for 7 consecutive days and deviates from the historical water usage pattern by more than 20%, the threshold calibration is triggered; in addition, the administrator can also manually update the threshold according to the needs of water supply policy adjustments and water meter maintenance. The updated system will take effect after one statistical cycle.

[0092] Abnormal signals are divided into level 1 abnormal signals, level 2 abnormal signals and level 3 abnormal signals based on their levels.

[0093] The first-level abnormal signal corresponds to the instantaneous flow rate sudden over-limit abnormality, which is triggered and output when the instantaneous water consumption peak exceeds the first proportional threshold of the peak threshold or the fluctuation coefficient exceeds a;

[0094] The secondary abnormal signal corresponds to a continuous abnormality in the cumulative amount or an abnormality in high-frequency water use. It is triggered and output when the daily growth rate of the cumulative water consumption exceeds the second proportional threshold of the daily growth rate of the cumulative water consumption for b consecutive days, or when the time interval between two adjacent water consumption times is lower than the third proportional threshold of the peak period interval threshold;

[0095] The third-level abnormal signal corresponds to abnormal trace continuous water use. It is triggered and output when the average flow rate during the night period is lower than the night flow threshold and the duration of a single water use during the night period exceeds the leakage duration threshold.

[0096] In one embodiment, abnormal signals are classified based on levels, including level one abnormal signals, level two abnormal signals, and level three abnormal signals. To ensure the accuracy and rationality of signal triggering, the triggering conditions for each level of abnormal signals are set as follows:

[0097] Level 1 abnormality signals correspond to sudden excess of instantaneous flow. This occurs when the peak value of instantaneous water consumption exceeds the first proportional threshold (150%) of the peak threshold. For example, if the peak threshold for residential users is set at 3 m³ / h, it is triggered when the instantaneous water consumption reaches 4.5 m³ / h or above. Alternatively, the fluctuation coefficient exceeds a (fixed value of 3.0), which means that the fluctuation amplitude of instantaneous water consumption is abnormally drastic. A level 1 abnormality signal is triggered when any of the above conditions are met. When both conditions occur simultaneously, the peak value is prioritized for handling as it has a more direct impact on the water supply system and poses a more urgent threat. In this case, a level 1 abnormality signal is output.

[0098] The secondary abnormal signal corresponds to a continuous abnormal accumulation or high-frequency water use. It is triggered when the daily growth rate of the cumulative water consumption exceeds the second proportional threshold (120%) of the daily growth rate threshold of the cumulative water consumption for b consecutive days (b=2). For example, if the daily growth rate threshold of the user's cumulative water consumption is 25%, it is triggered when the growth rate reaches 30% or above for two consecutive days, or when the time interval between two adjacent water uses is lower than the third proportional threshold (50%) of the peak period interval threshold. Assuming that the peak period interval threshold is 20 minutes, it is triggered when the time interval between two adjacent water uses is less than 10 minutes. It is triggered when any of the above conditions is met. When both conditions exist, it is triggered based on the cumulative water consumption daily growth rate exceeding the limit. At this time, the secondary abnormal signal is output.

[0099] The third-level abnormal signal corresponds to abnormally small amounts of continuous water use. When the average flow rate during the nighttime period (22:00 to 6:00 the next day) is lower than the nighttime flow threshold, for example, lower than 0.03m³ / h, and the duration of a single nighttime water use exceeds the leakage duration threshold (assuming the leakage duration threshold is 40 minutes), it is triggered when the single nighttime water use lasts for more than 40 minutes. The above two conditions must be met at the same time, without priority. Both conditions must be met at the same time, and neither condition alone is sufficient to determine a water leak. In this case, a third-level abnormal signal is output;

[0100] Abnormal signals can not only be upgraded, but also downgraded under certain conditions to more accurately reflect changes in water usage status. The specific rules are as follows:

[0101] The first-level abnormal signal corresponds to the instantaneous flow rate exceeding the limit abnormality. It is triggered and output when the instantaneous water consumption peak exceeds the first proportional threshold (150%) of the peak threshold or the fluctuation coefficient exceeds a (a=3.0). If, after the control measures are implemented, the instantaneous water consumption peak falls within 120% of the peak threshold within two consecutive verification cycles and the fluctuation coefficient drops below 2.5, it can be downgraded to a second-level abnormal signal.

[0102] Level 2 abnormal signals correspond to continuous abnormal accumulation or high-frequency water use. They are triggered and output when the daily growth rate of cumulative water consumption exceeds the second proportional threshold (120%) of the daily growth rate threshold for b consecutive days (b=2), or the time interval between two consecutive water use is lower than the third proportional threshold (50%) of the peak period interval threshold. If the daily growth rate of cumulative water consumption recovers to within 110% of the daily growth rate threshold within three days after the trigger, and the time interval between two consecutive water use recovers to more than 80% of the interval threshold during the peak period, the signal can be downgraded to a level 3 abnormal signal.

[0103] The third-level abnormal signal corresponds to abnormal trace continuous water use. It is triggered and output when the average flow rate during the night period is lower than the night flow threshold and the duration of a single water use during the night period exceeds the water leakage duration threshold. If, after the user responds to the prompt and fixes the problem, the average flow rate during the night period recovers to above the night flow threshold for three consecutive night periods, and the duration of a single water use is within the water leakage duration threshold, the abnormal signal can be lifted.

[0104] The preset warning rules include:

[0105] Level 1 abnormal signal uses a red warning sign;

[0106] Level 2 abnormal signal, using yellow warning sign;

[0107] Level 3 abnormal signal uses a blue warning sign.

[0108] In one embodiment, the preset warning rules include: a first-level abnormal signal, which uses a red warning logo and is presented in a striking flashing manner in the system interface. For example, on the system's main monitoring screen, the red warning logo will occupy the center of a specific area, attracting the administrator's attention through high-brightness flashing; a second-level abnormal signal, which uses a yellow warning logo and is displayed on the relevant page in a constantly bright and colorful form, so that the administrator can quickly detect it when browsing data reports. For example, at the top of the user's water use data details page, the yellow warning logo will intuitively prompt the user that there is a second-level abnormality; a third-level abnormal signal, which uses a blue warning logo and is displayed in a soft but still recognizable manner. For example, in the status bar of the user's personal water use information, the blue logo will continue to exist to remind the user of a third-level abnormality.

[0109] The warning module sends warning information to the administrator terminal in the form of pop-up windows and voice broadcasts, and simultaneously sends corresponding control instructions to the control module;

[0110] The early warning information includes abnormal signal level, abnormal type, abnormal occurrence time, and abnormal water usage data details.

[0111] In one embodiment, the early warning module sends the early warning information to the administrator terminal in the form of a pop-up window and voice broadcast, and simultaneously sends the corresponding control instructions to the control module; the early warning information includes the abnormal signal level, abnormal type, abnormal occurrence time and abnormal water use data details. The pop-up window is designed in a concise and clear format. The abnormal signal level is displayed in large font at the top of the pop-up window, and the abnormal type is described in a concise sentence, such as "instantaneous water consumption peak exceeds the limit". The abnormal occurrence time is accurate to the second, and the abnormal water use data details are presented in a table, listing the key data of the measured peak value of instantaneous water consumption, normal peak threshold and fluctuation coefficient. The voice broadcast uses clear and standard Mandarin pronunciation. The broadcast content first emphasizes the abnormal signal level, such as "level 1 abnormal signal", then explains the abnormal type, such as "sudden excessive water use abnormality", and finally informs the time of abnormal occurrence, such as "occurred at 10:25:40 am", so that the administrator can quickly know the key information.

[0112] The control instruction includes a first control instruction, a second control instruction and a third control instruction;

[0113] The control instruction priorities include:

[0114] The first control instruction has a high priority;

[0115] The second control instruction has medium priority;

[0116] The third control instruction has a low priority;

[0117] The first control instruction is to immediately close the smart water meter valve;

[0118] The second control instruction is to limit the instantaneous water flow to 50% of the rated flow value, which is the maximum allowable flow value preset when the smart water meter leaves the factory;

[0119] The third control instruction is to generate a water use abnormality prompt and push it to the user terminal.

[0120] In one embodiment, the control instruction includes a first control instruction, a second control instruction, and a third control instruction; the control instruction priorities include: the first control instruction is a high priority; the second control instruction is a medium priority; and the third control instruction is a low priority; the first control instruction is to immediately close the smart water meter valve; the second control instruction is to limit the instantaneous water flow to 50% of the rated flow value, where the rated flow value is the maximum allowable flow value preset when the smart water meter leaves the factory. The rated flow values ​​of water meters of different specifications are different. For example, the common DN15 (nominal diameter 15mm) specification water meter usually has a rated flow value of 3m³ / h, while the DN20 (nominal diameter 20mm) specification water meter may have a rated flow value of 5m³ / h; the third control instruction is to generate a water use abnormality prompt and push it to the user terminal. The prompt content includes a brief description of the abnormality type, such as "Your daily water consumption growth rate has exceeded the normal range for two consecutive days", and suggestions to guide the user to conduct a preliminary self-inspection, such as "Please check whether there is any water leak or abnormal water-using appliance in your home", and attach a water supply service hotline for user consultation.

[0121] Preset policies include:

[0122] When a first control instruction corresponding to a first-level abnormal signal is received, the smart water meter valve is immediately closed, and the water meter status is continuously monitored at intervals of c seconds after the valve is closed. If the abnormality is not resolved within d seconds and an abnormal signal is still detected, a second control instruction is triggered to temporarily limit the flow rate to a fourth proportional threshold of the rated flow value;

[0123] When the second control instruction corresponding to the second-level abnormal signal is received, the flow restriction operation is performed first, and the warning information is pushed to the user terminal simultaneously;

[0124] When the third control instruction corresponding to the third-level abnormal signal is received, only the water use abnormality prompt is sent to the user terminal, and the valve closing or flow restriction operation is not performed temporarily. If the user does not respond to the prompt within e hours, the abnormal signal level will be upgraded to a second-level abnormal signal and the second control instruction will be executed.

[0125] In one embodiment, when a first control instruction corresponding to a first-level abnormal signal is received, the smart water meter valve is immediately closed, and the water meter status is continuously monitored at intervals of c (c=1) seconds after the valve is closed. If the abnormality is not resolved within d (d=30) seconds and an abnormal signal is still detected, a second control instruction is triggered to temporarily limit the flow to the fourth proportional threshold (30%) of the rated flow value; when a second control instruction corresponding to a second-level abnormal signal is received, the flow restriction operation is performed first, and an early warning message is simultaneously pushed to the user terminal. The early warning message details the reason for the flow restriction as "Your water use has continued to be abnormal. In order to ensure stable water supply, the flow is temporarily restricted." The user is informed of the current flow value after the restriction and the expected time to return to normal, for example, "The current flow limit is 50% of the rated flow, that is, 1.5m³ / h per hour. We will continue to monitor and it is expected to return to normal after 24 hours." When a third control instruction corresponding to a third-level abnormal signal is received, only a water use abnormality prompt is sent to the user terminal, and the operation is not executed temporarily. In the case of valve closing or flow restriction operation, if the user does not respond to the prompt within e (e=24) hours, the abnormal signal level will be upgraded to a level 2 abnormal signal, and the second control instruction will be executed. The user's response to the prompt includes replying to the confirmation message in the mobile phone text message receiving the prompt, or clicking the "Understood" button in the official APP of the water supply company. Regarding the technical implementation of the user response method, in the Hongmeng system ecosystem, the mobile phone text message reply confirmation message relies on the communication framework of the Hongmeng system. When the user receives the abnormal prompt text message, the system automatically identifies the source of the text message as the smart water meter management system, and provides a quick reply template in the text message application. The user clicks on the corresponding template to complete the reply. The reply content is transmitted to the system server through the network module of the Hongmeng system. For the operation of clicking the "Understood" button in the official APP of the water supply company, the APP is based on the application development framework of the Hongmeng system. Through the long connection established with the server, the user click event and related user identification information are pushed to the server in real time to complete the recording and feedback of the user response.

[0126] After executing the control instruction, the timing function of the timing unit is used to periodically verify whether the abnormal signal is released according to the verification cycle, and determine whether to maintain, adjust or cancel the current control instruction based on the verification result;

[0127] The verification cycle includes:

[0128] The verification period for the first-level abnormal signal is f minutes;

[0129] The verification period for the secondary abnormal signal is g minutes;

[0130] The verification period for the third-level abnormal signal is h minutes;

[0131] The abnormal signal removal judgment adopts progressive verification rules, including basic data feature verification, water use data association verification and multi-water meter linkage verification;

[0132] Basic data feature verification: Within each verification cycle, the peak, average, and fluctuation coefficient of instantaneous water consumption are periodically extracted. The duration of a single water use, the time interval between two adjacent water uses, and the daily growth rate of cumulative water consumption are calculated and compared with the preset thresholds.

[0133] If any characteristic value is higher or lower than the corresponding preset threshold, the abnormal judgment is maintained and the basic data characteristic verification of the next verification cycle continues;

[0134] If all characteristic values ​​meet the corresponding threshold requirements, the water use data association verification is carried out;

[0135] If the water use data association verification triggers an exception, the basic data feature verification will be returned;

[0136] If the water usage data association verification does not trigger an exception, the multi-water meter linkage verification will begin;

[0137] Multi-meter linkage verification: During the verification period, wireless or wired communication technology is used to obtain data from regional water supply pipeline pressure sensors and water consumption data from other surrounding smart water meters;

[0138] During the same verification cycle, if the pipe network pressure fluctuation exceeds the first pressure fluctuation range threshold or the surrounding smart water meter exceeds the fifth ratio threshold and abnormal flow occurs, it is determined to be a regional problem, triggering an abnormal return to basic verification;

[0139] If only a single smart water meter is abnormal and the pipe network pressure is normal, it is determined to be a user-side problem, the abnormality is resolved, and the control instruction is revoked.

[0140] In one embodiment, the timing function of the timing unit is used to periodically verify whether the abnormal signal has been released according to the verification cycle, and determine whether to maintain, adjust or revoke the current control instruction based on the verification result. The verification cycle is positively correlated with the risk level of the abnormal signal level. The verification cycle of the first-level abnormal signal is f (f=5) minutes. For example, when a commercial user suddenly overuses water and triggers a first-level abnormal signal, high-frequency verification can quickly determine whether the valve closure is effective, avoiding long-term high-pressure operation of the pipeline. The verification cycle of the second-level abnormal signal is g (g=10) minutes, which is suitable for medium-risk scenarios with continuous abnormal cumulative water consumption. The verification cycle of the third-level abnormal signal is 30 minutes, which is used for non-emergency situations such as trace water leaks at night, reducing the pressure of low-value data processing.

[0141] The abnormal signal removal judgment adopts progressive verification rules, including basic data feature verification, water use data association verification and multi-water meter linkage verification;

[0142] Basic data feature verification: In each verification cycle, the peak, average, and fluctuation coefficient of instantaneous water consumption are collected, and the duration of a single water use, the time interval between two adjacent water uses, and the daily growth rate of cumulative water consumption are calculated. These are compared item by item with the corresponding preset thresholds, including the peak value must be less than or equal to the preset peak threshold, the fluctuation coefficient must be less than or equal to the preset fluctuation coefficient threshold, and the daily growth rate must be less than or equal to the preset daily growth rate threshold. If any characteristic value is higher or lower than its corresponding preset threshold, for example, the peak value reaches 4m³ / h and exceeds the preset peak threshold of 3m³ / h, the abnormal judgment is maintained and the next cycle verification is continued; if all characteristic values ​​meet the corresponding threshold requirements, for example, the measured peak value of 2.8m³ / h is less than or equal to 3m³ / h and the fluctuation coefficient of 1.8 is less than or equal to the preset value of 3.0), then the water use data association verification is entered;

[0143] Water usage data is associated and verified by converting timestamps, instantaneous flow rates, and water meter identifiers into a structured table. Timestamps are accurate to the minute, and instantaneous flow rates include low (less than or equal to 0.1 m³ / h), medium (0.1-1 m³ / h), and high (greater than 1 m³ / h). Appliance identifiers are categorized by type, such as kitchen faucets and water heaters. 15-minute granularity data is then extracted during peak hours. The percentage of instantaneous flow peaks and durations with instantaneous flow rates greater than 0.5 m³ / h, as well as deviations from the mean of the previous three years, are counted. If the deviation rate is greater than 20%, it is marked as an anomaly. The deviation ΔQ of the water consumption over the past seven days from the mean of the previous three years (ΔQ = | sliding mean - Historical mean | / historical mean × 100%)), when ΔQ is greater than 15% and the proportion of water consumption at night exceeds the normal range (10% ± 5%), an early warning is triggered; then, based on the historical data of 1,000 households, a typical associated scenario is preset, that is, the night flow rate is less than 0.03m³ / h and the water consumption lasts for more than 40 minutes. Under this condition, 80% of water leakage events will trigger an alarm, and after confirmation, 90% of them are real water leakage. For example, the night flow threshold is set to 0.03m³ / h, the leakage duration threshold is set to 40 minutes, and the peak flow rate during peak hours is greater than 80% of the rated flow rate. % and the interval is less than 10 minutes (the support degree of this rule is 75% and the confidence degree is 85%). If any scenario is met, an anomaly is triggered. Finally, if the deviation of the water consumption of a single user from the area average is greater than 25%, the pressure sensor data is combined with a sudden drop greater than 0.1MPa to determine a pipe network problem and the abnormal proportion of water meters in the same area is greater than 30% to determine a regional peak. If a single water meter is abnormal, the user-side verification phase is entered. If the water data association verification triggers an anomaly, the basic data feature verification is returned. If the water data association verification does not trigger an anomaly, the multi-meter linkage verification phase is entered.

[0144] For multi-water meter linkage verification, when the water supply area is open and wiring is difficult but the real-time data requirements are high, NB-IoT wireless connection is selected to obtain the data of the regional water supply pipe pressure sensor deployed at the water supply network branch. The data is collected once per second. The pressure sensor is installed at the network branch every 50 meters and connected to the data collector through the NB-IoT wireless module. If there is an existing wired network infrastructure in the water supply area and the data security requirements are high, RS-485 wired connection is selected. The pressure sensor is connected to the data collector through the RS-485 wired interface. At the same time, the water consumption data of all water meters in the same water supply subnet are obtained. The water meter data complies with DL / T 645-2007 communication protocol, uploaded to the cloud platform through the MQTT protocol, the pipe network pressure fluctuation threshold is ±0.1MPa. Based on the analysis of the historical pressure data of the urban water supply system, it can effectively identify more than 90% of the abnormal pipe network fluctuation scenarios. If the pressure sensor shows that the pipe network pressure drops by 0.2MPa, exceeding the first pressure fluctuation range threshold (±0.1MPa), or the surrounding water meters above the fifth ratio threshold (30%) have abnormal flow, it is determined to be a regional problem, triggering the abnormal return to basic verification; if a single water meter is abnormal and the pressure is normal, it is determined to be abnormal water use on the user side, the abnormality is resolved and the control instruction is revoked.

[0145] The present invention uses multi-dimensional feature extraction and sliding window algorithm, combined with historical data and industry standards to dynamically adjust the threshold, accurately identify abnormal water use, and reduce the false alarm rate compared with traditional solutions. The threshold can be automatically calibrated according to the season and water use trend. It adopts a three-level abnormal signal classification, and pushes it in real time through pop-up windows and voice, shortening the response time to minutes. The control instructions are linked with the level to avoid "one size fits all". With the help of Hongmeng's distributed communication capabilities, multi-device data is obtained in real time. Combined with progressive verification rules, it distinguishes between user-side and regional anomalies, improves positioning accuracy, and realizes user terminal linkage based on the Hongmeng ecosystem, guides autonomous investigation, and reduces operation and maintenance costs. The hardware unifies the protocol through the HDF driver framework, reduces expansion costs, and significantly improves system maintainability.

[0146] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0147] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. The smart water meter management system based on open source Hongmeng is characterized by: include: Analysis module, early warning module and control module; The analysis module is used to obtain raw data, extract features and perform analysis, generate analysis results, perform monitoring based on preset monitoring rules, and output an abnormality signal when the analysis result shows an abnormality and transmit it to the early warning module; The warning module, after receiving the abnormal signal, generates warning information according to the preset warning rules and sends it to the administrator terminal, and simultaneously generates control instructions according to the warning information and sends them to the control module; The control module controls the smart water meter according to the preset strategy based on the control instruction and performs verification; The abnormal signals are divided into level 1 abnormal signals, level 2 abnormal signals and level 3 abnormal signals based on the level of the abnormal signals; The first-level abnormal signal corresponds to the instantaneous flow rate sudden over-limit abnormality, which is triggered and output when the instantaneous water consumption peak exceeds the first proportional threshold of the peak threshold or the fluctuation coefficient exceeds a; The secondary abnormal signal corresponds to a continuous abnormality in the cumulative amount or an abnormality in high-frequency water use, and is triggered and output when the daily growth rate of the cumulative water consumption exceeds the second proportional threshold of the daily growth rate threshold of the cumulative water consumption for b consecutive days, or when the time interval between two adjacent water consumptions is lower than the third proportional threshold of the peak period interval threshold; The third-level abnormal signal corresponds to abnormal trace continuous water use, which is triggered and output when the average flow rate during the night period is lower than the night flow threshold and the duration of a single water use during the night period exceeds the water leakage duration threshold; The preset strategies include: When a first control instruction corresponding to a first-level abnormal signal is received, the smart water meter valve is immediately closed, and the water meter status is continuously monitored at intervals of c seconds after the valve is closed. If the abnormality is not resolved within d seconds and an abnormal signal is still detected, a second control instruction is triggered to temporarily limit the flow rate to a fourth proportional threshold of the rated flow value; When the second control instruction corresponding to the second-level abnormal signal is received, the flow restriction operation is performed first, and the warning information is pushed to the user terminal simultaneously; When the third control instruction corresponding to the third-level abnormal signal is received, only the water use abnormality prompt is sent to the user terminal, and the valve closing or flow restriction operation is not performed temporarily. If the user does not respond to the prompt within e hours, the abnormal signal level is upgraded to the second-level abnormal signal and the second control instruction is executed; After executing the control instruction, the timing function of the timing unit is used to periodically verify whether the abnormal signal is released according to the verification period, and determine whether to maintain, adjust or cancel the current control instruction based on the verification result; The verification cycle includes: The verification period for the first-level abnormal signal is f minutes; The verification period for the secondary abnormal signal is g minutes; The verification period for the third-level abnormal signal is h minutes; The abnormal signal removal judgment adopts a progressive verification rule, specifically including basic data feature verification, water use data association verification and multi-water meter linkage verification; The basic data feature verification is to periodically extract the peak value, average value and fluctuation coefficient of instantaneous water consumption within each verification cycle, calculate the duration of a single water use, the time interval between two adjacent water uses and the daily growth rate of cumulative water consumption, and compare them with the preset threshold value; If any characteristic value is higher or lower than the corresponding preset threshold, the abnormal judgment is maintained and the basic data characteristic verification of the next verification cycle continues; If all characteristic values ​​meet the corresponding threshold requirements, the water use data association verification is carried out; If the water use data association verification triggers an exception, return to the basic data feature verification; If the water usage data association verification does not trigger an exception, the multi-water meter linkage verification is performed; The multi-water meter linkage verification obtains the regional water supply pipeline pressure sensor data and the water consumption data of other surrounding smart water meters through wireless communication technology or wired communication technology during the verification period; During the same verification cycle, if the pipe network pressure fluctuation exceeds the first pressure fluctuation range threshold or the surrounding smart water meter exceeds the fifth ratio threshold and abnormal flow occurs, it is determined to be a regional problem, triggering an abnormal return to basic verification; If only a single smart water meter is abnormal and the pipe network pressure is normal, it is determined to be a user-side problem, the abnormality is resolved, and the control instruction is revoked.

2. The smart water meter management system based on open source Hongmeng as claimed in claim 1 is characterized by: The raw data includes instantaneous water consumption, cumulative water consumption and water consumption time data; The instantaneous water consumption is collected by the built-in flow sensor of the smart water meter; The accumulated water consumption and water use time data are collected by a timing unit.

3. The smart water meter management system based on open source Hongmeng as claimed in claim 2 is characterized by: Extracting and analyzing features of the raw data to generate analysis results specifically includes: Extracting the peak value, average value and fluctuation coefficient of the instantaneous water consumption; Calculate the duration of a single water use; Count the time interval between two adjacent water use; Extract the average flow rate during night time; Calculate the daily growth rate of the cumulative water consumption; When any characteristic value exceeds the corresponding preset threshold, an abnormal signal is output to the early warning module; The characteristic values ​​include peak value, average value, fluctuation coefficient, duration of single water use, time interval between two adjacent water uses, average flow rate during night time and daily growth rate of cumulative water use.

4. The smart water meter management system based on open source Hongmeng as claimed in claim 3 is characterized by: The preset thresholds include: Instantaneous water consumption thresholds, including peak thresholds, fluctuation coefficient thresholds, and nighttime flow thresholds; Cumulative water consumption thresholds, including daily growth rate thresholds; Water usage time data thresholds include: Water use time interval thresholds, including peak hour interval thresholds and nighttime interval thresholds; Water usage duration threshold, including the maximum duration threshold for a single water use and the water leakage duration threshold.

5. The smart water meter management system based on open source Hongmeng as claimed in claim 4 is characterized by: The preset warning rules include: Level 1 abnormal signal uses a red warning sign; Level 2 abnormal signal uses yellow warning sign; Level 3 abnormal signal uses a blue warning sign.

6. The smart water meter management system based on open source Hongmeng as claimed in claim 5 is characterized by: The warning module sends the warning information to the administrator terminal in the form of pop-up windows and voice broadcasts, and simultaneously sends corresponding control instructions to the control module; The warning information includes abnormal signal level, abnormal type, abnormal occurrence time, and abnormal water usage data details.

7. The smart water meter management system based on open source Hongmeng as claimed in claim 6 is characterized by: The control instructions include a first control instruction, a second control instruction and a third control instruction; The control instruction priorities include: The first control instruction has a high priority; The second control instruction has a medium priority; The third control instruction has a low priority; The first control instruction is to immediately close the smart water meter valve; The second control instruction is to limit the instantaneous water flow to 50% of the rated flow value, and the rated flow value is the maximum allowable flow value preset when the smart water meter leaves the factory; The third control instruction is to generate a water use abnormality prompt and push it to the user terminal.

Images